Energy Demand Forecasting Model Performance Report

The following report contains model performance metrics for the NY City Hourly Probabilistic Residential Energy Demand Forecasting Pipeline. Model performance was evaluated on both long-term and day-ahead forecasts. Evaluation was conducted using a holdout dataset of hourly energy demand values between 2023-09-26 and 2024-04-27.

Long-Term Forecasting Performance

The following table contains performance metrics for the forecasting model compared with a yearly moving average baseline model.
MSE Weighted MSE MAE MAPE Wilcoxon Test p-value
Forecasting Pipeline 128742.60 126301.35 270.23 0.05 0.0
Baseline Yearly MA 604819.81 604819.81 626.46 0.13 NaN

The following Plotly Figure helps to contextualize the forecasting model's performance by showing its predictions along with the actual energy demand values. It also presents the 95% confidence interval bounds estimated by the forecasting model.



Day-Ahead Forecasting Performance

The following table contains performance metrics for the forecasting model compared with a yearly moving average baseline model.
MSE Weighted MSE MAE MAPE Wilcoxon Test p-value
Forecasting Pipeline 121216.29 121213.86 265.82 0.05 NaN
Baseline Moving Avg 353146.56 353146.56 515.37 0.10 0.0
EIA Forecasts 113145.06 NaN 291.30 0.06 0.0

The following Plotly Figure helps to contextualize the forecasting model's performance by showing its predictions along with the actual energy demand values. It also presents the 95% confidence interval bounds estimated by the forecasting model.



Model Sensitivity Analysis

The following data has been made up for demonstration purposes. Actual data will be provided in a future update.

Sensitivity Analysis